MIMOmics

This is a blog about MIMOmics (Methods for Integrated analysis of multiple Omics datasets), an FP7-HEALTH-2012 Innovation project funded by the European Commission, running from October 2012 till October 2017, coordinated by the Leiden University Medical Center.

Mittwoch, 10. Februar 2016

Welcome to the MIMOmics blog!

This blog is intended as a forum for all partners in this project to discuss current research, and present new and exciting results.

To briefly summarise what this project is about, here is a quote from the project website:

MIMOmics develops statistical
methods for the integrated analysis of metabolomics, proteomics,
glycomics and genomic datasets in large studies. Our project is based on
our involvement in studies participating in EU funded projects, i.e. GEHA, IDEAL, Mark-Age, ENGAGE and EuroSpan.
In these consortia the primary goal is to identify molecular profiles
that monitor and explain complex traits with novel findings so far.
Support for methodological development is missing. The state-of-the-art
methodology does not match by far the complexity of the biological
problem. Complex data are being analysed in a rather simple way which
misses the opportunity to uncover combinations of predictive profiles
among the omics data.

The objectives of MIMOmics are:

to develop a statistical framework of methods for all analysis steps
needed for identifying and interpreting omics-based biomarkers

to integrate data derived from multiple omics platforms across several study designs and populations.

The following recurrent epidemiological questions will be answered:

which molecular profiles are associated?

can we identify subgroups of patients based on molecular profiles?

which biological pathways play a role?

which informative marker profiles within each population can be transferred across populations?

are the identified molecular marker profiles causal?

To perform these tasks successfully we bring together established EU
academic and industrial researchers in metabolomics, glycomics,
biostatistics, bioinformatics, scientific computing and epidemiology,
with complementary expertise. A key feature of our project is the
validation of novel methodology by performing a proof of principle
(Metabolic Health). Special effort will be made for rapid uptake of
methods by communication with associated consortia and development of
user-friendly software.